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This is the numerical bottom-up optimization model used in
St�ckl, F. and A. Zerrahn (2020): Substituting Clean for Dirty Energy: A Bottom-Up Analysis

This model is derived from
The Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER).
Version 1.3.0, November 2018.
Written by Alexander Zerrahn and Wolf-Peter Schill.

This work is licensed under the MIT License (MIT).
For more information on this license, visit http://opensource.org/licenses/mit-license.php.
Whenever you use this code, please refer to http://www.diw.de/dieter.
We are happy to receive feedback under azerrahn@diw.de and wschill@diw.de.
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**** Scenario file                   ****
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Parameter
m_exog_p(n,tech)
m_exog_sto_e(n,sto)
m_exog_sto_p_in(n,sto)
m_exog_sto_p_out(n,sto)
;

m_exog_p(n,tech) = technology_data(n,tech,'fixed_capacities') ;
m_exog_sto_e(n,sto) = storage_data(n,sto,'fixed_capacities_energy');
m_exog_sto_p_in(n,sto) = storage_data(n,sto,'fixed_capacities_power_in');
m_exog_sto_p_out(n,sto) = storage_data(n,sto,'fixed_capacities_power_out');

N_TECH.up(n,tech) = m_exog_p(n,tech) ;
N_STO_P_IN.up(n,sto) = m_exog_sto_p_in(n,sto) ;
N_STO_P_OUT.up(n,sto) = m_exog_sto_p_out(n,sto) ;
N_STO_E.up(n,sto) = m_exog_sto_e(n,sto) ;